Overview

Dataset statistics

Number of variables31
Number of observations4807996
Missing cells13887314
Missing cells (%)9.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 GiB
Average record size in memory248.0 B

Variable types

CAT15
NUM15
BOOL1

Warnings

dat_cadastramento_fam has a high cardinality: 4960 distinct values High cardinality
dat_alteracao_fam has a high cardinality: 1364 distinct values High cardinality
dat_atualizacao_familia has a high cardinality: 1376 distinct values High cardinality
nom_estab_assist_saude_fam has a high cardinality: 25584 distinct values High cardinality
nom_centro_assist_fam has a high cardinality: 3699 distinct values High cardinality
cod_centro_assist_fam is highly correlated with cd_ibgeHigh correlation
cd_ibge is highly correlated with cod_centro_assist_famHigh correlation
qtd_comodos_domic_fam has 224026 (4.7%) missing values Missing
qtd_comodos_dormitorio_fam has 222998 (4.6%) missing values Missing
cod_material_piso_fam has 222349 (4.6%) missing values Missing
cod_material_domic_fam has 222349 (4.6%) missing values Missing
cod_agua_canalizada_fam has 222349 (4.6%) missing values Missing
cod_abaste_agua_domic_fam has 222349 (4.6%) missing values Missing
cod_banheiro_domic_fam has 222349 (4.6%) missing values Missing
cod_escoa_sanitario_domic_fam has 494595 (10.3%) missing values Missing
cod_destino_lixo_domic_fam has 222349 (4.6%) missing values Missing
cod_iluminacao_domic_fam has 222349 (4.6%) missing values Missing
cod_calcamento_domic_fam has 222350 (4.6%) missing values Missing
nom_estab_assist_saude_fam has 2441370 (50.8%) missing values Missing
cod_eas_fam has 2441370 (50.8%) missing values Missing
nom_centro_assist_fam has 3031030 (63.0%) missing values Missing
cod_centro_assist_fam has 3031030 (63.0%) missing values Missing
ind_parc_mds_fam has 155334 (3.2%) missing values Missing
id_familia has unique values Unique
vlr_renda_media_fam has 494189 (10.3%) zeros Zeros
ind_parc_mds_fam has 4244511 (88.3%) zeros Zeros

Reproduction

Analysis started2020-09-11 19:22:31.342201
Analysis finished2020-09-11 19:37:08.374775
Duration14 minutes and 37.03 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

cd_ibge
Real number (ℝ≥0)

HIGH CORRELATION

Distinct5534
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2993741.547
Minimum1100015
Maximum5300108
Zeros0
Zeros (%)0.0%
Memory size36.7 MiB
2020-09-11T16:37:08.513568image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1100015
5-th percentile1501303
Q12311875.25
median2927002
Q33526209
95-th percentile5101803
Maximum5300108
Range4200093
Interquartile range (IQR)1214333.75

Descriptive statistics

Standard deviation937280.9281
Coefficient of variation (CV)0.3130801085
Kurtosis0.1068486716
Mean2993741.547
Median Absolute Deviation (MAD)604801
Skewness0.393206125
Sum1.439389738e+13
Variance8.784955382e+11
MonotocityNot monotonic
2020-09-11T16:37:08.653370image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
35503082332304.9%
 
3304557983602.0%
 
2304400733961.5%
 
2927408600271.2%
 
1302603454670.9%
 
1501402409500.9%
 
2611606384050.8%
 
2111300356630.7%
 
3106200292790.6%
 
5300108285380.6%
 
Other values (5524)412468185.8%
 
ValueCountFrequency (%) 
1100015361< 0.1%
 
110002327530.1%
 
110003155< 0.1%
 
11000492259< 0.1%
 
1100056271< 0.1%
 
ValueCountFrequency (%) 
5300108285380.6%
 
5222302153< 0.1%
 
522220350< 0.1%
 
5222054169< 0.1%
 
5222005175< 0.1%
 

estrato
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.7 MiB
2
4085981 
1
722015 
ValueCountFrequency (%) 
2408598185.0%
 
172201515.0%
 
2020-09-11T16:37:08.773685image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-11T16:37:08.846769image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:37:08.916362image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

classf
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.7 MiB
3
2856584 
2
1023594 
1
927818 
ValueCountFrequency (%) 
3285658459.4%
 
2102359421.3%
 
192781819.3%
 
2020-09-11T16:37:09.020364image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-11T16:37:09.097307image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:37:09.173879image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

id_familia
Real number (ℝ≥0)

UNIQUE

Distinct4807996
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2709538.437
Minimum1
Maximum5290701
Zeros0
Zeros (%)0.0%
Memory size36.7 MiB
2020-09-11T16:37:11.650561image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile284955.75
Q11393348.75
median2739219.5
Q34049591.25
95-th percentile5044434.25
Maximum5290701
Range5290700
Interquartile range (IQR)2656242.5

Descriptive statistics

Standard deviation1530538.528
Coefficient of variation (CV)0.5648705724
Kurtosis-1.204976871
Mean2709538.437
Median Absolute Deviation (MAD)1327558
Skewness-0.04921304009
Sum1.302744997e+13
Variance2.342548186e+12
MonotocityStrictly increasing
2020-09-11T16:37:11.783613image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
16109791< 0.1%
 
19420541< 0.1%
 
19420221< 0.1%
 
19420241< 0.1%
 
19420261< 0.1%
 
19420281< 0.1%
 
19420301< 0.1%
 
19420321< 0.1%
 
19420351< 0.1%
 
19420371< 0.1%
 
Other values (4807986)4807986> 99.9%
 
ValueCountFrequency (%) 
11< 0.1%
 
31< 0.1%
 
41< 0.1%
 
61< 0.1%
 
71< 0.1%
 
ValueCountFrequency (%) 
52907011< 0.1%
 
52907001< 0.1%
 
52906991< 0.1%
 
52906981< 0.1%
 
52906971< 0.1%
 

dat_cadastramento_fam
Categorical

HIGH CARDINALITY

Distinct4960
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Memory size36.7 MiB
2003-03-13
 
144547
2002-08-18
 
9396
2003-08-04
 
8886
2002-05-22
 
8314
2002-07-20
 
8105
Other values (4955)
4628747 
ValueCountFrequency (%) 
2003-03-131445473.0%
 
2002-08-1893960.2%
 
2003-08-0488860.2%
 
2002-05-2283140.2%
 
2002-07-2081050.2%
 
2006-04-0877380.2%
 
2006-04-0174210.2%
 
2006-08-1972850.2%
 
2002-09-0771570.1%
 
2002-07-0568310.1%
 
Other values (4950)459231595.5%
 
2020-09-11T16:37:11.942636image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique524 ?
Unique (%)< 0.1%
2020-09-11T16:37:12.063554image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length9.999998544
Min length3

dat_alteracao_fam
Categorical

HIGH CARDINALITY

Distinct1364
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.7 MiB
2018-10-01
1654010 
2018-09-30
1433585 
2018-10-02
218865 
2018-09-25
 
21591
2018-09-27
 
19269
Other values (1359)
1460676 
ValueCountFrequency (%) 
2018-10-01165401034.4%
 
2018-09-30143358529.8%
 
2018-10-022188654.6%
 
2018-09-25215910.4%
 
2018-09-27192690.4%
 
2018-11-13166250.3%
 
2018-11-27162630.3%
 
2018-11-28161410.3%
 
2018-12-11160120.3%
 
2018-12-04159020.3%
 
Other values (1354)137973328.7%
 
2020-09-11T16:37:12.199303image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique62 ?
Unique (%)< 0.1%
2020-09-11T16:37:12.320445image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10

vlr_renda_media_fam
Real number (ℝ≥0)

ZEROS

Distinct2806
Distinct (%)0.1%
Missing138
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean279.7731331
Minimum0
Maximum2862
Zeros494189
Zeros (%)10.3%
Memory size36.7 MiB
2020-09-11T16:37:12.434095image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q133
median100
Q3440
95-th percentile954
Maximum2862
Range2862
Interquartile range (IQR)407

Descriptive statistics

Standard deviation350.8036979
Coefficient of variation (CV)1.253886297
Kurtosis3.140338859
Mean279.7731331
Median Absolute Deviation (MAD)100
Skewness1.685596758
Sum1345109496
Variance123063.2345
MonotocityNot monotonic
2020-09-11T16:37:12.561161image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
049418910.3%
 
9542123854.4%
 
502074304.3%
 
9372003184.2%
 
1001266282.6%
 
751120832.3%
 
4771034402.2%
 
66918831.9%
 
25827151.7%
 
33780551.6%
 
Other values (2796)309873264.4%
 
ValueCountFrequency (%) 
049418910.3%
 
1126080.3%
 
2216560.5%
 
3154490.3%
 
4236360.5%
 
ValueCountFrequency (%) 
286261< 0.1%
 
28612< 0.1%
 
28605< 0.1%
 
28594< 0.1%
 
28581< 0.1%
 

dat_atualizacao_familia
Categorical

HIGH CARDINALITY

Distinct1376
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.7 MiB
2018-09-13
 
17127
2018-09-11
 
16350
2018-09-12
 
16257
2018-11-13
 
15519
2018-09-04
 
15451
Other values (1371)
4727292 
ValueCountFrequency (%) 
2018-09-13171270.4%
 
2018-09-11163500.3%
 
2018-09-12162570.3%
 
2018-11-13155190.3%
 
2018-09-04154510.3%
 
2018-11-28149420.3%
 
2018-09-10148980.3%
 
2018-08-07148840.3%
 
2018-11-12148550.3%
 
2018-11-21148520.3%
 
Other values (1366)465286196.8%
 
2020-09-11T16:37:12.722279image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique32 ?
Unique (%)< 0.1%
2020-09-11T16:37:12.846099image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10
Distinct2
Distinct (%)< 0.1%
Missing20727
Missing (%)0.4%
Memory size36.7 MiB
1
3852815 
2
934454 
ValueCountFrequency (%) 
1385281580.1%
 
293445419.4%
 
(Missing)207270.4%
 
2020-09-11T16:37:12.941603image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-11T16:37:13.008273image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:37:13.075456image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3
Distinct3
Distinct (%)< 0.1%
Missing20730
Missing (%)0.4%
Memory size36.7 MiB
1
4585649 
2
 
161167
3
 
40450
ValueCountFrequency (%) 
1458564995.4%
 
21611673.4%
 
3404500.8%
 
(Missing)207300.4%
 
2020-09-11T16:37:13.174801image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-11T16:37:13.246179image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:37:13.320652image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

qtd_comodos_domic_fam
Real number (ℝ≥0)

MISSING

Distinct21
Distinct (%)< 0.1%
Missing224026
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean4.418609851
Minimum0
Maximum20
Zeros184
Zeros (%)< 0.1%
Memory size36.7 MiB
2020-09-11T16:37:13.417868image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q14
median5
Q35
95-th percentile7
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.380896982
Coefficient of variation (CV)0.3125184229
Kurtosis1.64972056
Mean4.418609851
Median Absolute Deviation (MAD)1
Skewness0.2039207811
Sum20254775
Variance1.906876475
MonotocityNot monotonic
2020-09-11T16:37:13.528252image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%) 
5161875733.7%
 
4111438423.2%
 
370040514.6%
 
652548310.9%
 
23100406.4%
 
71502723.1%
 
1833071.7%
 
8548741.1%
 
9158280.3%
 
1065540.1%
 
Other values (11)40660.1%
 
(Missing)2240264.7%
 
ValueCountFrequency (%) 
0184< 0.1%
 
1833071.7%
 
23100406.4%
 
370040514.6%
 
4111438423.2%
 
ValueCountFrequency (%) 
2069< 0.1%
 
1920< 0.1%
 
1834< 0.1%
 
1727< 0.1%
 
1655< 0.1%
 

qtd_comodos_dormitorio_fam
Real number (ℝ≥0)

MISSING

Distinct20
Distinct (%)< 0.1%
Missing222998
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean1.775068386
Minimum0
Maximum20
Zeros1999
Zeros (%)< 0.1%
Memory size36.7 MiB
2020-09-11T16:37:13.644300image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q32
95-th percentile3
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7538018879
Coefficient of variation (CV)0.4246607589
Kurtosis17.08510656
Mean1.775068386
Median Absolute Deviation (MAD)1
Skewness1.569846723
Sum8138685
Variance0.5682172861
MonotocityNot monotonic
2020-09-11T16:37:13.746123image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%) 
2217514745.2%
 
1176677036.7%
 
356655111.8%
 
4609781.3%
 
596460.2%
 
62382< 0.1%
 
01999< 0.1%
 
7553< 0.1%
 
8240< 0.1%
 
12162< 0.1%
 
Other values (10)570< 0.1%
 
(Missing)2229984.6%
 
ValueCountFrequency (%) 
01999< 0.1%
 
1176677036.7%
 
2217514745.2%
 
356655111.8%
 
4609781.3%
 
ValueCountFrequency (%) 
20157< 0.1%
 
183< 0.1%
 
175< 0.1%
 
161< 0.1%
 
1547< 0.1%
 

cod_material_piso_fam
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing222349
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean3.586297637
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size36.7 MiB
2020-09-11T16:37:13.846880image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median5
Q35
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.537008739
Coefficient of variation (CV)0.4285781312
Kurtosis-1.715803855
Mean3.586297637
Median Absolute Deviation (MAD)0
Skewness-0.1741459638
Sum16445495
Variance2.362395864
MonotocityNot monotonic
2020-09-11T16:37:13.928826image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
5230268547.9%
 
2182959538.1%
 
11857823.9%
 
41672883.5%
 
3702361.5%
 
7268720.6%
 
631890.1%
 
(Missing)2223494.6%
 
ValueCountFrequency (%) 
11857823.9%
 
2182959538.1%
 
3702361.5%
 
41672883.5%
 
5230268547.9%
 
ValueCountFrequency (%) 
7268720.6%
 
631890.1%
 
5230268547.9%
 
41672883.5%
 
3702361.5%
 

cod_material_domic_fam
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)< 0.1%
Missing222349
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean1.540680955
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size36.7 MiB
2020-09-11T16:37:14.020226image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.233464673
Coefficient of variation (CV)0.8005970794
Kurtosis11.39308843
Mean1.540680955
Median Absolute Deviation (MAD)0
Skewness3.219770058
Sum7065019
Variance1.5214351
MonotocityNot monotonic
2020-09-11T16:37:14.111053image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
1336552970.0%
 
269055514.4%
 
32742085.7%
 
6768911.6%
 
5627661.3%
 
8605051.3%
 
4499371.0%
 
752560.1%
 
(Missing)2223494.6%
 
ValueCountFrequency (%) 
1336552970.0%
 
269055514.4%
 
32742085.7%
 
4499371.0%
 
5627661.3%
 
ValueCountFrequency (%) 
8605051.3%
 
752560.1%
 
6768911.6%
 
5627661.3%
 
4499371.0%
 

cod_agua_canalizada_fam
Categorical

MISSING

Distinct2
Distinct (%)< 0.1%
Missing222349
Missing (%)4.6%
Memory size36.7 MiB
1
4023381 
2
562266 
ValueCountFrequency (%) 
1402338183.7%
 
256226611.7%
 
(Missing)2223494.6%
 
2020-09-11T16:37:14.221702image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-11T16:37:14.290313image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:37:14.360332image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

cod_abaste_agua_domic_fam
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing222349
Missing (%)4.6%
Memory size36.7 MiB
1
3537937 
2
693380 
4
 
211057
3
 
143273
ValueCountFrequency (%) 
1353793773.6%
 
269338014.4%
 
42110574.4%
 
31432733.0%
 
(Missing)2223494.6%
 
2020-09-11T16:37:14.464356image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-11T16:37:14.538028image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:37:14.620791image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

cod_banheiro_domic_fam
Categorical

MISSING

Distinct2
Distinct (%)< 0.1%
Missing222349
Missing (%)4.6%
Memory size36.7 MiB
1
4313401 
2
 
272246
ValueCountFrequency (%) 
1431340189.7%
 
22722465.7%
 
(Missing)2223494.6%
 
2020-09-11T16:37:14.722521image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-11T16:37:14.797606image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:37:14.867475image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

cod_escoa_sanitario_domic_fam
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing494595
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean1.864986585
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size36.7 MiB
2020-09-11T16:37:14.950133image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile3
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.04023785
Coefficient of variation (CV)0.5577722962
Kurtosis0.6721160173
Mean1.864986585
Median Absolute Deviation (MAD)0
Skewness0.9832491488
Sum8044435
Variance1.082094784
MonotocityNot monotonic
2020-09-11T16:37:15.038591image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
1225775847.0%
 
3124405425.9%
 
264898913.5%
 
4880821.8%
 
5428990.9%
 
6316190.7%
 
(Missing)49459510.3%
 
ValueCountFrequency (%) 
1225775847.0%
 
264898913.5%
 
3124405425.9%
 
4880821.8%
 
5428990.9%
 
ValueCountFrequency (%) 
6316190.7%
 
5428990.9%
 
4880821.8%
 
3124405425.9%
 
264898913.5%
 

cod_destino_lixo_domic_fam
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing222349
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean1.409208123
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size36.7 MiB
2020-09-11T16:37:15.126803image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum6
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8344851491
Coefficient of variation (CV)0.5921660085
Kurtosis3.966479432
Mean1.409208123
Median Absolute Deviation (MAD)0
Skewness2.023718151
Sum6462131
Variance0.6963654641
MonotocityNot monotonic
2020-09-11T16:37:15.223262image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
1357597074.4%
 
366527713.8%
 
22625435.5%
 
4620821.3%
 
6180410.4%
 
51734< 0.1%
 
(Missing)2223494.6%
 
ValueCountFrequency (%) 
1357597074.4%
 
22625435.5%
 
366527713.8%
 
4620821.3%
 
51734< 0.1%
 
ValueCountFrequency (%) 
6180410.4%
 
51734< 0.1%
 
4620821.3%
 
366527713.8%
 
22625435.5%
 

cod_iluminacao_domic_fam
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing222349
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean1.317827343
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size36.7 MiB
2020-09-11T16:37:15.310878image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum6
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9058275392
Coefficient of variation (CV)0.6873643534
Kurtosis13.16471092
Mean1.317827343
Median Absolute Deviation (MAD)0
Skewness3.515250495
Sum6043091
Variance0.8205235307
MonotocityNot monotonic
2020-09-11T16:37:15.405989image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
1388836780.9%
 
22793855.8%
 
32710035.6%
 
6863911.8%
 
4379060.8%
 
5225950.5%
 
(Missing)2223494.6%
 
ValueCountFrequency (%) 
1388836780.9%
 
22793855.8%
 
32710035.6%
 
4379060.8%
 
5225950.5%
 
ValueCountFrequency (%) 
6863911.8%
 
5225950.5%
 
4379060.8%
 
32710035.6%
 
22793855.8%
 

cod_calcamento_domic_fam
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing222350
Missing (%)4.6%
Memory size36.7 MiB
1
2720352 
3
1579965 
2
285329 
ValueCountFrequency (%) 
1272035256.6%
 
3157996532.9%
 
22853295.9%
 
(Missing)2223504.6%
 
2020-09-11T16:37:15.507974image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-11T16:37:15.572080image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:37:15.648751image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size36.7 MiB
2
4782826 
1
 
25168
ValueCountFrequency (%) 
2478282699.5%
 
1251680.5%
 
(Missing)2< 0.1%
 
2020-09-11T16:37:16.509856image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-11T16:37:16.584320image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:37:16.652232image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3
Distinct2
Distinct (%)< 0.1%
Missing25170
Missing (%)0.5%
Memory size36.7 MiB
2
4753516 
1
 
29310
ValueCountFrequency (%) 
2475351698.9%
 
1293100.6%
 
(Missing)251700.5%
 
2020-09-11T16:37:16.743758image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-11T16:37:16.807870image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:37:16.875957image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

nom_estab_assist_saude_fam
Categorical

HIGH CARDINALITY
MISSING

Distinct25584
Distinct (%)1.1%
Missing2441370
Missing (%)50.8%
Memory size36.7 MiB
CLINICA DA FAMILIA
 
19037
POSTO DE COLETA DE CODO I
 
4212
HOSPITAL MUNICIPAL JAMEL CECILIO ANAPOLIS
 
4014
UNIDADE DE SAUDE FAMILIAR COMUNITARIA
 
2451
HOSPITAL MUNICIPAL DE IPIRA
 
2044
Other values (25579)
2334868 
ValueCountFrequency (%) 
CLINICA DA FAMILIA190370.4%
 
POSTO DE COLETA DE CODO I42120.1%
 
HOSPITAL MUNICIPAL JAMEL CECILIO ANAPOLIS40140.1%
 
UNIDADE DE SAUDE FAMILIAR COMUNITARIA24510.1%
 
HOSPITAL MUNICIPAL DE IPIRA2044< 0.1%
 
UBS DE SANTALUZ2021< 0.1%
 
C S F ARGEU HERBSTER1783< 0.1%
 
UNIDADE MISTA DE AFUA1775< 0.1%
 
SECRETARIA MUNICIPAL DA SAUDE DE IJUI VIGILANCIA EM SAUDE1773< 0.1%
 
CENTRO DE SAUDE SAO FRANCISCO1753< 0.1%
 
Other values (25574)232576348.4%
 
(Missing)244137050.8%
 
2020-09-11T16:37:17.063697image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1795 ?
Unique (%)0.1%
2020-09-11T16:37:17.210045image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length60
Median length3
Mean length16.06854561
Min length3

cod_eas_fam
Real number (ℝ≥0)

MISSING

Distinct27005
Distinct (%)1.1%
Missing2441370
Missing (%)50.8%
Infinite0
Infinite (%)0.0%
Mean3075005.845
Minimum19
Maximum9630546
Zeros0
Zeros (%)0.0%
Memory size36.7 MiB
2020-09-11T16:37:17.363920image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile24473
Q12290278
median2533979
Q33182738
95-th percentile6874053
Maximum9630546
Range9630527
Interquartile range (IQR)892460

Descriptive statistics

Standard deviation1707394.582
Coefficient of variation (CV)0.5552492151
Kurtosis1.603776376
Mean3075005.845
Median Absolute Deviation (MAD)297072
Skewness1.245833164
Sum7.277388783e+12
Variance2.915196258e+12
MonotocityNot monotonic
2020-09-11T16:37:17.496730image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
6310354190310.4%
 
302343542120.1%
 
236174440140.1%
 
265396624510.1%
 
40266402044< 0.1%
 
25110882021< 0.1%
 
24823471783< 0.1%
 
23160481775< 0.1%
 
68595341773< 0.1%
 
24820881710< 0.1%
 
Other values (26995)232581248.4%
 
(Missing)244137050.8%
 
ValueCountFrequency (%) 
1933< 0.1%
 
3510< 0.1%
 
43386< 0.1%
 
51400< 0.1%
 
8618< 0.1%
 
ValueCountFrequency (%) 
96305463< 0.1%
 
96186942< 0.1%
 
96149901< 0.1%
 
96147451< 0.1%
 
95984051< 0.1%
 

nom_centro_assist_fam
Categorical

HIGH CARDINALITY
MISSING

Distinct3699
Distinct (%)0.2%
Missing3031030
Missing (%)63.0%
Memory size36.7 MiB
CRAS CENTRO DE REFERENCIA DE ASSISTENCIA SOCIAL
 
39099
CRAS CENTRO
 
34910
CRAS CENTRO DE REFERENCIA DA ASSISTENCIA SOCIAL
 
26266
CRAS
 
16197
CENTRO DE REFERENCIA DE ASSISTENCIA SOCIAL
 
14565
Other values (3694)
1645929 
ValueCountFrequency (%) 
CRAS CENTRO DE REFERENCIA DE ASSISTENCIA SOCIAL390990.8%
 
CRAS CENTRO349100.7%
 
CRAS CENTRO DE REFERENCIA DA ASSISTENCIA SOCIAL262660.5%
 
CRAS161970.3%
 
CENTRO DE REFERENCIA DE ASSISTENCIA SOCIAL145650.3%
 
CRAS I145450.3%
 
CRAS CENTRAL144180.3%
 
CENTRO DE REFERENCIA DA ASSISTENCIA SOCIAL134810.3%
 
CRAS CASA DA FAMILIA109520.2%
 
CRAS GRAJAU105540.2%
 
Other values (3689)158197932.9%
 
(Missing)303103063.0%
 
2020-09-11T16:37:17.649635image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique186 ?
Unique (%)< 0.1%
2020-09-11T16:37:17.805180image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length70
Median length3
Mean length10.13874242
Min length3

cod_centro_assist_fam
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct5639
Distinct (%)0.3%
Missing3031030
Missing (%)63.0%
Infinite0
Infinite (%)0.0%
Mean3.16930602e+10
Minimum1.10001204e+10
Maximum5.300109833e+10
Zeros0
Zeros (%)0.0%
Memory size36.7 MiB
2020-09-11T16:37:17.946872image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1.10001204e+10
5-th percentile1.40010365e+10
Q12.510800679e+10
median3.304550065e+10
Q33.550303288e+10
95-th percentile5.006600139e+10
Maximum5.300109833e+10
Range4.200097794e+10
Interquartile range (IQR)1.039502609e+10

Descriptive statistics

Standard deviation9529194109
Coefficient of variation (CV)0.3006713158
Kurtosis-0.155210341
Mean3.16930602e+10
Median Absolute Deviation (MAD)5981499146
Skewness-0.04535792694
Sum5.63174904e+16
Variance9.080554037e+19
MonotocityNot monotonic
2020-09-11T16:37:18.073854image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
3.550303288e+10105540.2%
 
3.550300162e+10104470.2%
 
3.550300165e+1089150.2%
 
3.550303289e+1076560.2%
 
2.30370012e+1072200.2%
 
3.550300177e+1069990.1%
 
3.550300167e+1069980.1%
 
3.55030018e+1062910.1%
 
3.550300168e+1061440.1%
 
3.550300163e+1060000.1%
 
Other values (5629)169974235.4%
 
(Missing)303103063.0%
 
ValueCountFrequency (%) 
1.10001204e+10357< 0.1%
 
1.100020668e+10350< 0.1%
 
1.100051504e+1056< 0.1%
 
1.100061099e+1026< 0.1%
 
1.100070427e+1098< 0.1%
 
ValueCountFrequency (%) 
5.300109833e+1027< 0.1%
 
5.300109755e+1014< 0.1%
 
5.300109754e+104< 0.1%
 
5.30010967e+102< 0.1%
 
5.30010373e+10406< 0.1%
 

ind_parc_mds_fam
Real number (ℝ≥0)

MISSING
ZEROS

Distinct13
Distinct (%)< 0.1%
Missing155334
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean19.30041168
Minimum0
Maximum306
Zeros4244511
Zeros (%)88.3%
Memory size36.7 MiB
2020-09-11T16:37:18.186793image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile205
Maximum306
Range306
Interquartile range (IQR)0

Descriptive statistics

Standard deviation63.21474913
Coefficient of variation (CV)3.275305739
Kurtosis8.191045388
Mean19.30041168
Median Absolute Deviation (MAD)0
Skewness3.102432982
Sum89798292
Variance3996.104508
MonotocityNot monotonic
2020-09-11T16:37:18.279414image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%) 
0424451188.3%
 
2052630945.5%
 
202432160.9%
 
301252180.5%
 
204241600.5%
 
306228090.5%
 
303103420.2%
 
20187320.2%
 
30545350.1%
 
30424620.1%
 
Other values (3)35830.1%
 
(Missing)1553343.2%
 
ValueCountFrequency (%) 
0424451188.3%
 
1011810< 0.1%
 
20187320.2%
 
202432160.9%
 
2031041< 0.1%
 
ValueCountFrequency (%) 
306228090.5%
 
30545350.1%
 
30424620.1%
 
303103420.2%
 
302732< 0.1%
 

marc_pbf
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.7 MiB
1
2424434 
0
2383562 
ValueCountFrequency (%) 
1242443450.4%
 
0238356249.6%
 
2020-09-11T16:37:18.354224image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

qtde_pessoas
Real number (ℝ≥0)

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.687830855
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Memory size36.7 MiB
2020-09-11T16:37:18.422562image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile5
Maximum31
Range30
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.442161182
Coefficient of variation (CV)0.53655206
Kurtosis1.471999579
Mean2.687830855
Median Absolute Deviation (MAD)1
Skewness0.9751546479
Sum12923080
Variance2.079828875
MonotocityNot monotonic
2020-09-11T16:37:18.515348image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%) 
2130066427.1%
 
3115577724.0%
 
1112213423.3%
 
472630015.1%
 
53099436.4%
 
61202892.5%
 
7448310.9%
 
8171880.4%
 
967520.1%
 
1026000.1%
 
Other values (9)1518< 0.1%
 
ValueCountFrequency (%) 
1112213423.3%
 
2130066427.1%
 
3115577724.0%
 
472630015.1%
 
53099436.4%
 
ValueCountFrequency (%) 
311< 0.1%
 
183< 0.1%
 
173< 0.1%
 
165< 0.1%
 
1518< 0.1%
 

peso.fam
Real number (ℝ≥0)

Distinct886
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.21170859e+14
Minimum5.501656235e+12
Maximum5.504777045e+14
Zeros0
Zeros (%)0.0%
Memory size36.7 MiB
2020-09-11T16:37:18.632683image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum5.501656235e+12
5-th percentile5.502917229e+13
Q15.502215892e+14
median5.502451463e+14
Q35.502540234e+14
95-th percentile5.503448472e+14
Maximum5.504777045e+14
Range5.449760482e+14
Interquartile range (IQR)3.243417885e+10

Descriptive statistics

Standard deviation1.170883957e+14
Coefficient of variation (CV)0.2246641263
Kurtosis12.33229392
Mean5.21170859e+14
Median Absolute Deviation (MAD)1.243471773e+10
Skewness-3.783180996
Sum-2.969788772e+18
Variance1.370969241e+28
MonotocityNot monotonic
2020-09-11T16:37:18.759281image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
5.502451463e+1483980717.5%
 
5.502443092e+142332304.9%
 
5.50245607e+141216862.5%
 
5.50243164e+14983602.0%
 
5.502477921e+14733961.5%
 
5.502458232e+14666341.4%
 
5.502484072e+13600271.2%
 
5.502427962e+14503971.0%
 
5.502457847e+14492541.0%
 
5.502430102e+14454670.9%
 
Other values (876)316973865.9%
 
ValueCountFrequency (%) 
5.501656235e+1224270.1%
 
5.501682233e+121464< 0.1%
 
5.5018315e+121769< 0.1%
 
5.502526708e+12153690.3%
 
5.50304564e+12508< 0.1%
 
ValueCountFrequency (%) 
5.504777045e+146< 0.1%
 
5.504449465e+141337< 0.1%
 
5.504443495e+141082< 0.1%
 
5.504410327e+14983< 0.1%
 
5.504395098e+141186< 0.1%
 

Interactions

2020-09-11T16:33:58.752976image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:33:59.152102image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:33:59.487635image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:33:59.819948image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:00.173340image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:00.503445image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:00.818701image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:01.139122image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:01.458464image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:01.779206image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:02.099057image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:02.408305image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:02.712897image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:03.049857image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:03.372074image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:03.678854image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:03.979932image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:04.299943image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:04.625261image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:04.963057image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:34:05.299585image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
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2020-09-11T16:35:13.240734image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2020-09-11T16:37:18.924435image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-09-11T16:37:19.267421image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-09-11T16:37:19.614420image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-09-11T16:37:19.957004image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-09-11T16:37:20.264703image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-09-11T16:35:23.285098image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:35:39.921492image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:36:52.268151image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-11T16:36:59.725432image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Sample

First rows

cd_ibgeestratoclassfid_familiadat_cadastramento_famdat_alteracao_famvlr_renda_media_famdat_atualizacao_familiacod_local_domic_famcod_especie_domic_famqtd_comodos_domic_famqtd_comodos_dormitorio_famcod_material_piso_famcod_material_domic_famcod_agua_canalizada_famcod_abaste_agua_domic_famcod_banheiro_domic_famcod_escoa_sanitario_domic_famcod_destino_lixo_domic_famcod_iluminacao_domic_famcod_calcamento_domic_famcod_familia_indigena_famind_familia_quilombola_famnom_estab_assist_saude_famcod_eas_famnom_centro_assist_famcod_centro_assist_famind_parc_mds_fammarc_pbfqtde_pessoaspeso.fam
03205002221.02018-06-282018-10-02244.02018-06-281.01.05.02.05.01.01.01.01.01.02.01.01.02.02.0NaNNaNCRAS DE SERRA SEDE3.205003e+100.005550256458545518
13205101223.02018-08-272018-11-2960.02018-11-291.01.05.02.05.01.01.01.01.01.01.01.01.02.02.0NaNNaNCRAS VIANA3.205103e+100.015550355704647837
23201308224.02018-02-232018-02-27937.02018-02-231.01.04.01.02.02.01.01.01.01.01.01.03.02.02.0NaNNaNCRAS IV ALTO MUCURI3.201300e+100.001550259704488172
33201308226.02013-12-272018-10-0144.02017-06-221.01.04.01.02.02.01.01.01.01.01.02.03.02.02.0US CAMPO VERDE2652994.0CRAS III CAMPO VERDE3.201300e+100.012550259704488172
43205002227.02018-03-262018-03-280.02018-03-261.01.04.01.05.01.02.04.01.05.03.01.03.02.02.0UNIDADE REGIONAL DE SAUDE SERRA2465795.0NaNNaN0.012550256458545518
53205002228.02016-10-272018-10-01176.02016-10-271.01.06.03.05.01.01.01.01.01.01.01.02.02.02.0UNIDADE BASICA DE SAUDE VILA NOVA DE COLARES2522845.0CRAS DE VILA NOVA DE COLARES3.205000e+100.015550256458545518
63205200229.02015-06-162018-10-01312.02018-03-201.01.05.02.05.01.01.01.01.03.01.01.03.02.02.0UNIDADE DE SAUDE DA FAMILIA DE ULISSES GUIMARAES3346501.0CRAS JABAETE3.205202e+100.003550245146328323
732013082210.02017-04-052018-10-01954.02018-07-041.01.01.01.05.01.01.01.01.01.01.02.01.02.02.0NaNNaNCRAS VII SOTELANDIA3.201304e+100.001550259704488172
832052002211.02018-10-032018-10-15477.02018-10-031.01.05.02.05.01.01.01.01.01.01.01.01.02.02.0UNIDADE DE SAUDE DA FAMILIA DE TERRA VERMELHA2403412.0CRAS MORADA DA BARRA3.205200e+100.002550245146328323
932050022212.02016-05-112016-05-114.02016-05-111.01.01.01.05.01.01.01.01.01.01.01.01.02.02.0NaNNaNNaNNaN0.013550256458545518

Last rows

cd_ibgeestratoclassfid_familiadat_cadastramento_famdat_alteracao_famvlr_renda_media_famdat_atualizacao_familiacod_local_domic_famcod_especie_domic_famqtd_comodos_domic_famqtd_comodos_dormitorio_famcod_material_piso_famcod_material_domic_famcod_agua_canalizada_famcod_abaste_agua_domic_famcod_banheiro_domic_famcod_escoa_sanitario_domic_famcod_destino_lixo_domic_famcod_iluminacao_domic_famcod_calcamento_domic_famcod_familia_indigena_famind_familia_quilombola_famnom_estab_assist_saude_famcod_eas_famnom_centro_assist_famcod_centro_assist_famind_parc_mds_fammarc_pbfqtde_pessoaspeso.fam
48079863550308215290692.02018-11-222018-11-221400.02018-11-221.01.02.01.05.01.01.01.01.01.01.01.01.02.02.0NaNNaNCRAS JACANA3.550300e+100.001550244309203512
48079873550308215290693.02018-01-102018-10-01468.02018-01-101.01.04.01.05.01.01.01.01.01.01.01.01.02.02.0UBS J VISTA ALEGRE2787946.0CRAS BRASILANDIA II3.550304e+100.002550244309203512
48079883550308215290694.02015-02-122018-10-1530.02018-10-151.01.05.02.05.01.01.01.01.01.01.01.01.02.02.0NaNNaNCRAS ITAIM PAULISTA II3.550304e+100.015550244309203512
48079893550308215290695.02014-12-032018-10-01436.02017-11-211.01.03.01.05.01.01.01.01.01.01.02.01.02.02.0NaNNaNCRAS ARTHUR ALVIM3.550303e+100.003550244309203512
48079903550308215290696.02017-09-132018-10-24217.02018-10-241.01.03.01.05.01.01.01.01.01.01.01.01.02.02.0AMA UBS INTEGRADA JARDIM HELENA4049934.0CRAS SAO MIGUEL3.550300e+100.003550244309203512
48079913550308215290697.02018-07-302018-10-021129.02018-07-301.01.02.01.05.01.01.01.01.01.01.01.01.02.02.0NaNNaNCRAS CIDADE LIDER3.550303e+100.001550244309203512
48079923550308215290698.02018-02-162018-10-010.02018-02-161.01.08.05.05.01.01.01.01.01.01.01.01.02.02.0UBS INTEGRAL JARDIM MIRIAM II7128940.0CRAS CIDADE ADEMAR II3.550304e+100.011550244309203512
48079933550308215290699.02014-10-092018-10-01162.02017-10-041.01.03.01.05.01.01.01.01.01.01.01.01.02.02.0NaNNaNCRAS JABAQUARA3.550300e+100.004550244309203512
48079943550308215290700.02006-05-242018-09-3083.02017-08-151.01.03.01.05.01.01.01.01.01.01.03.01.02.02.0UBS J NAKAMURA2787644.0CRAS M BOI MIRIM3.550300e+100.011550244309203512
48079953550308215290701.02015-05-142018-10-01445.02017-08-021.01.04.02.05.01.01.01.01.01.01.01.01.02.02.0UBS VARGINHA2789299.0CRAS GRAJAU3.550303e+100.003550244309203512